productivity assessment and improvement measurement of ... - Eric

International Symposium on Stochastic Models in Reliability Engineering, Life Sciences and Operations Management (SMRLO'10)

PRODUCTIVITY ASSESSMENT AND IMPROVEMENT MEASUREMENT OF DECISION MAKING UNITS - AN APPLICATION FOR RANKING CITIES IN ISRAEL

Yossi HADAD Prof., Industrial Engineering and Management Department, SCE - Shamoon College of Engineering, Beer-Sheva, Israel

E-mail: [email protected]

Baruch KEREN PhD, Industrial Engineering and Management Department, SCE - Shamoon College of Engineering, Beer-Sheva, Israel


Avner BEN-YAIR PhD, Center for Reliability and Risk Management, SCE - Shamoon College of Engineering, Beer-Sheva, Israel


Abstract: In this paper we will demonstrate how productivity and improvement rate of urban organizational units (called also Decision Making Units - DMU's) may be assessed when measured along several time periods. The assessment and subsequent ranking of cities is achieved by means of the Data Envelopment Analysis (DEA) methodology to determine DMU's efficiency for each period, the Cross Efficiency ranking method to rank DMU's and the Malmquist Index approach which measures changes in productivity relative to a base period. The above combined methodology will be applied to a case study of 70 Israeli cities in years 2006, 2007 and 2008.

Key words: Data Envelopment Analysis (DEA); Malmquist Index; ranking methods

409

International Symposium on Stochastic Models in Reliability Engineering, Life Sciences and Operations Management (SMRLO'10) 1. Introduction Banks, insurance companies, widespread food chains, police stations, etc., are organizations that have several branches and subunits (Decision Making Units - DMUs). Such organizations are often interested in assessing the productivity of their DMU's in two main aspects: 1) Relative efficiency of each DMU per every time period; 2) General improvement trends among DMU's. The importance of this assessment boils down to first know better relative productivity of each DMU as compared to other structural units, and in addition to be aware of improvement trends characteristic of every DMU. Profound knowledge of the above parameters enables decision makers in the regarded organizations to assess better specific performance of each division unit as well as their timely changes, thus contributing to a broader managerial view on every DMU within the organization. In our application we assume that cities are subunits of the organization, and therefore their relative productivities and their improvement trends should be estimated. Relative efficiency of each DMU (productivity assessment) for every time period may be investigated by means of the DEA methodology (the so-called CCR or BCC models) which have been primarily suggested by Charnes, Cooper and Rhodes (CCR) in 1978 and subsequently developed and expanded by Banker, Charnes and Cooper (BCC) in 1984. The CCR model calculates the Technical and Scale Efficiency (TSE) while BCC determines Technical Efficiency (TE). In addition to that, productivity assessment may be facilitated by means of conventional ranking methods, like the Super Efficiency method (SE) developed by Anderson and Peterson (1993), the Cross Efficiency method (CE) introduced by Sexton et al. (1994), the bi-criteria method for efficient DMU ranking suggested by Hadad and Friedman (2004), as well as a combination of the AHP method (Analytical Hierarchic Process) and the DEA methodology described by Sinuany-Stern et al. (2000). A comprehensive review of contemporary ranking methods can be found in a study by Adler et al. (2002). In recent years, a variety of scientific papers tackling the problem of productivity assessment by means of DEA and ranking methods, have been published and are available to the broad scientific community. Among others, one should mention Sueyoshi (1992) who measured the industrial performance of 35 Chinese cities by means of Data Envelopment Analysis, Doyle and Green (1994) who ranked 20 universities in the UK; Hadad, et al. (2009), to carry out comparative efficiency assessment and ranking of public defence authority in Israel; Malul, et al. (2009), measuring and ranking of economic, environmental and social efficiency of countries; Hadad, et al. (2007), measuring efficiency of restaurants; Hadad, et al. (2004), evaluating hotel advertisements efficiency using DEA; Hadad, et al. (2004), ranking fish farms. Relative improvement trend for each DMU may be assessed when comparing productivities determined for every pair of consecutive time periods, or by means of Malmquist Index approach primarily suggested by Caves, et al. (1982) and subsequently developed by Fare, et al. (1985) and Fare, et al. (1994). This method investigates the improvement measure of each DMU during every pair of consecutive time periods. Should the amount of time periods exceed 2, the procedure boils down to determining improvement levels for consecutive time periods with subsequently calculating the mean geometrical product for all values obtained during the regarded complex time period (Coelli, (1996)). Practical implementation of the Malmquist Index approach have been demonstrated by Barros (2006) who investigated relative efficiency of 33 police stations in Lisbon during

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International Symposium on Stochastic Models in Reliability Engineering, Life Sciences and Operations Management (SMRLO'10) 2001-2002. In his research, Barros also estimates the total productivity change of the Lisbon Police Force. In the present paper, we will demonstrate joint implementation of the DEA methodology, the Cross Efficiency ranking method and the Malmquist Index approach for productivity assessment of 70 Israeli cities between 2006-2008. The cities will be estimated every year separately upon a variety of parameters which we will regard as inputs or outputs. In addition, we will verify existence of positive correlation between the productivity ratios calculated by means of the Cross Efficiency method versus the Malmquist Index approach. Our paper is organized in the following way. The next section introduces the presentation and formulation of DEA procedures, which will be employed in the analysis and the Super Efficiency. The third section presents the Malmquist Index approach. Part four illustrates how to evaluate city advertisements’ efficiency using the models that have been described in sections two and three. Finally, the findings are presented along with conclusions and recommendations for future research.

2. Data Envelopment Analysis and Cross Efficiency 2.1. Data Envelopment Analysis DEA is a procedure designed to measure the relative efficiency in situations when there are multiple inputs and multiple outputs and no obvious objective how to aggregate both inputs and outputs into a meaningful index of productive efficiency DEA was developed by Charnes Cooper and Rhodes (CCR) (1978). The method provides a mechanism for measuring the efficiency of each Decision-Making Unit (DMU). The efficiency in CCR model is termed Technical and Scale Efficiency (TSE) and the relative efficiency of a DMU is defined as the ratio of its total weighted output to its total weighted input. The BCC model, named after Banker, Charnes and Cooper (1984) allow the production function to exhibit non-constant return to scale (Banker and Chang 1995)) whiles the CCR model imposes the additional assumption of constant returns to scale on the production function. The formulation of CCR model for unit k is: Maximize

hk =

s

∑U Y r =1

k r rk

subject to s

m

r =1

i =1

∑UrkYrj − ∑Vik Xij ≤ 0 for j = 1,2,..,n, m

∑V X i =1

k

i

ik

(1)

= 1,

Urk ≥ ε > 0

r = 1,2,..,s ,

Vik ≥ ε > 0

i = 1,2,...,m.

where ε is defined as an infinitesimal constant (a non-Archimedean quantity).

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International Symposium on Stochastic Models in Reliability Engineering, Life Sciences and Operations Management (SMRLO'10) 2.2. The Cross Efficiency The Cross Evaluation matrix was first developed by Sexton et al. (1994). This method calculated the efficiency score of each unit n times using the optimal weights evaluated by each run. The results of all the DEA cross efficiency are summarized in a matrix as given in (2) s

hkj =

∑U

k r

∑V

k

r =1 m

,

i

i =1

Yrj

j = 1,2,..., n , k = 1,2,..., n .

(2)

X ij

Thus hkj represents the score given to unit j by the optimal weights of unit k . The elements in the diagonal hkk represent the standard DEA scores hk . The Cross Efficiency ranking method utilized the matrix hkj for ranking the units one scale. Ranking of DMUs is thus based on the average cross efficiency score being calculated as n

hk =

∑h

kj

j =1

n

.

3. The Malmquist Index Approach To investigate improvement of productivity, Fare et al. (1994) have demonstrated that DEA methodology may be applied to assess Malmquist Total Factor Productivity (TFP) index numbers. As a matter of fact, Malmquist index is an approach enabling relative measurement of productivity changes between consecutive periods of time (e.g., a year). Those productivity changes may be broken down to structural elements depending on technical efficiency enhancement as well as technology changes and progress. The Malmquist DEA approach determines efficiency level in a certain year relatively to the previous one, thus enabling evaluation of productivity improvement between the two consecutive periods. The Malmquist TFP index measures efficiency in each period t related to the base period s in terms of productivity improvement. Fare et al. (1994) specifies an output based Malmquist productivity change index: 1

⎡ d s (y , x ) d t (y , x ) ⎤ 2 m0 ( y s , x s , y t , xt ) = ⎢ 0s t t × 0t t t ⎥ ⎣ d 0 ( y s , x s ) d 0 ( y s , x s )⎦

(3)

where the notations d 0 ( yt , xt ) , d 0 ( y t , xt ) , d 0 ( y s , xs ) , d 0 ( y s , x s ) are distance s

functions and x ,

t

s

t

y are the output and input vector.

An equivalent way of writing this would be 1

d t ( y , x ) ⎡ d s ( y , x ) d t ( y , x )⎤ 2 m0 ( y s , x s , y t , xt ) = 0s t t ⎢ 0s t t × 0t s s ⎥ . d 0 ( y s , x s ) ⎣ d 0 ( y t , xt ) d 0 ( y s , x s ) ⎦

(4)

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International Symposium on Stochastic Models in Reliability Engineering, Life Sciences and Operations Management (SMRLO'10) The above equation can be broken into two parts, namely the efficiency change component and the technical change component:

Efficiency change =

d 0t ( y t , xt ) d 0s ( y s , x s )

(5)

and 1

⎡ d s ( y , x ) d t ( y , x )⎤ 2 Technical change = ⎢ 0s t t × 0t s s ⎥ . ⎣ d 0 ( y t , xt ) d 0 ( y s , x s ) ⎦

(6)

The Malmquist productivity change index may be determined as the result of solving 4 linear programming problems as listed below:

⎧d 0s ( y t , xt ) = min θ ⎪ ⎪⎪subject to ⎨ − y ot + Ys λ ≥ 0 ⎪ θx − X λ ≥ 0 0t s ⎪ ⎪⎩ λ≥0 ⎧d 0t ( y t , xt ) = min θ ⎪ ⎪⎪subject to ⎨ − y os + Ys λ ≥ 0 ⎪ θx − X λ ≥ 0 0s s ⎪ ⎪⎩ λ≥0 In (7-10),

θ

is a scalar,

λ

(7)

⎧d 0s ( y s , x s ) = min θ ⎪ ⎪⎪subject to ⎨ − y os + Ys λ ≥ 0 ⎪ θx − X λ ≥ 0 0s s ⎪ ⎪⎩ λ≥0

(8)

(9)

⎧d 0t ( y t , xt ) = min θ ⎪ ⎪⎪subject to ⎨ − y ot + Yt λ ≥ 0 ⎪ θx − X λ ≥ 0 0t t ⎪ ⎪⎩ λ≥0

(10)

is a vector that representative the constants. The value

of θ will be the efficiency score for the i -th DMU. It will satisfy θ less than or equal to 1, with a value of 1 indicating a point on the frontier and hence a technically efficient DMU. These four LPs must be solved for each DMU in the sample.

4. The Case Study on Israeli Cities 4.1. Determining DMUs In order to proceed with the DEA procedure one has to determine first Decision Making Units (DMUs). In our research, we decided to determine DMUs as Israeli cities comprising a total of 10,000 inhabitants at least. The latter data has been adopted from the Central Bureau Statistics database published in 2006, 2007, 2008. 4.2. Selection of outputs and inputs An important issue in employing DEA is the selection of inputs and outputs. In order to calculate the efficiency and the score of each city entering this study the following outputs and inputs have been implemented: Inputs

X 1 - negative emigration percentage - the ratio between citizens that left the city to the total number of inhabitants (negative emigration ratio);

X 2 - percentage of unemployed citizens and obtaining minimal income insurance;

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International Symposium on Stochastic Models in Reliability Engineering, Life Sciences and Operations Management (SMRLO'10)

X 3 - percentage of deceased throughout the year; X 4 - average number of schoolchildren in a classroom;

X 5 - average number of apartments per citizen; X 6 - average spending by the local authority per citizen (in thousands NIS per citizen). Outputs

Y1 - positive immigration percentage - the ratio between citizens that joint the city to the total number of inhabitants (positive immigration ratio);

Y2 - average monthly income per citizen (in thousands NIS per month);

Y3 - percentage of successfully graduating from the city school system that complied with university entrance requirements;

Y4 - average number of private vehicles per citizen;

Y5 - average city income per citizen (including donations from the state). We will demonstrate the regarded procedure for Year 2008. The data on 70 cities with 5 outputs and 6 inputs are given in Table 1: Table 1. The numerical data for 2008 City

Year

X1

X2

X3

X4

X5

X6

Y1

Y2

Y3

Y4

Y5

Umm el-Faheim 2008 0.41% 16.21% 0.30% 30.25 0.28 4107.84 0.11% 3588.11 23.00% 0.1977 12924.81 OFAKIM

2008 3.77% 14.35% 0.55% 20.91 0.24 5863.73 0.09% 4182.77 37.60% 0.1604 17231.31

Or Yehuda

2008 3.53% 5.73% 0.49% 25.19 0.30 6250.42 0.11% 5706.27 43.60% 0.3121 20275.02

Or Akiva

2008 3.89% 8.03% 0.88% 21.25 0.31 6461.46 0.08% 4445.78 43.60% 0.2429 20919.81

Eilat

2008 10.99% 5.12% 0.32% 25.94 0.35 13736.39 0.10% 5334.78 51.80% 0.2974 39797.78

Ariel

2008 4.76% 3.51% 0.44% 27.52 0.28 6098.48 0.07% 5480.70 39.90% 0.2406 20728.72

Ashdod

2008 2.37% 8.54% 0.57% 26.61 0.29 5156.99 0.10% 5590.69 46.50% 0.1952 17595.95

Ashkelon

2008 2.84% 11.52% 0.69% 28.62 0.32 4692.72 0.10% 4989.72 49.40% 0.2343 16448.67

BakaJat

2008 0.76% 4.28% 0.34% 30.89 0.23 15958.20 0.08% 4275.78 41.00% 0.2457 55935.87

Beer-Sheva

2008 3.46% 10.95% 0.68% 26.22 0.37 5711.99 0.06% 5515.36 43.60% 0.2252 19125.60

Beit-Shean

2008 2.54% 9.35% 0.51% 20.99 0.28 9391.22 0.10% 4530.72 42.20% 0.2471 23928.66

Beit-Shemesh

2008 3.37% 4.07% 0.27% 24.07 0.22 3904.86 0.13% 5187.96 31.30% 0.1227 13059.96

Beitar-Illit

2008 2.49% 4.11% 0.10% 23.42 0.19 4100.62 0.19% 3345.32 25.30% 0.0523 10698.04

Bney-Brak

2008 3.74% 4.25% 0.46% 25.73 0.26 5249.03 0.08% 4613.07 36.00% 0.5272 17272.95

Bat-Yam

2008 4.73% 5.73% 0.99% 26.37 0.37 5314.27 0.09% 4755.76 42.50% 0.2486 17487.41

Givatayim

2008 6.40% 1.76% 0.92% 30.63 0.45 6798.70 0.11% 8775.23 66.30% 0.3988 21178.30

Dimona

2008 3.19% 15.87% 0.70% 24.51 0.33 5676.74 0.06% 5677.29 35.70% 0.1778 18799.31

Hod-Hasharon 2008 3.74% 1.42% 0.36% 28.36 0.31 6234.17 0.14% 9580.47 66.10% 0.3808 20975.07 Herzliya

2008 4.48% 1.90% 0.70% 27.34 0.39 8773.56 0.09% 8637.24 64.10% 0.4884 29958.56

Hadera

2008 3.06% 5.82% 0.75% 26.32 0.34 6128.19 0.10% 5492.21 44.60% 0.2937 19964.86

Holon

2008 3.67% 3.46% 0.72% 27.65 0.36 5580.70 0.09% 6013.82 53.10% 0.3474 18974.67

Haifa

2008 3.18% 7.38% 0.99% 25.49 0.42 8035.95 0.08% 7030.48 60.00% 0.3541 26247.90

Tiberias

2008 4.20% 12.19% 0.55% 24.13 0.35 8101.73 0.06% 4381.15 35.90% 0.2428 22693.33

Taibe

2008 0.34% 14.00% 0.38% 31.61 0.20 9559.56 0.13% 3898.18 30.90% 0.2393 26776.78

Tierra

2008 0.44% 3.60% 0.35% 28.73 0.25 3817.01 0.14% 3934.20 40.60% 0.2806 11242.56

Tirat-Carmel

2008 2.93% 10.66% 0.84% 22.98 0.33 7091.02 0.06% 4829.38 46.90% 0.2474 25790.75

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International Symposium on Stochastic Models in Reliability Engineering, Life Sciences and Operations Management (SMRLO'10) City

Year

X1

X2

X3

X4

X5

X6

Y1

Y2

Y3

Y4

Y5

Tamra

2008 0.44% 21.37% 0.33% 29.18 0.23 5344.81 0.11% 3621.48 36.30% 0.2158 16442.14

Yavne

2008 3.66% 6.82% 0.42% 26.17 0.28 6130.53 0.07% 6679.61 51.70% 0.3398 22593.32

Yehud

2008 4.30% 2.25% 0.48% 28.56 0.32 10237.37 0.10% 8353.91 61.50% 0.3870 26502.27

Jerusalem

2008 2.35% 3.66% 0.44% 26.23 0.25 4900.07 0.06% 5699.61 31.60% 0.2057 15893.69

Kfar-Saba

2008 4.13% 1.95% 0.68% 28.27 0.31 6634.08 0.09% 7856.73 68.10% 0.4168 20607.02

Karmiel

2008 3.49% 6.95% 0.68% 27.16 0.34 4962.59 0.09% 5732.54 51.80% 0.2510 17681.90

Lod

2008 4.09% 9.07% 0.69% 25.79 0.30 4856.54 0.07% 5015.39 37.10% 0.4340 16640.97

Migdal-Haemeq 2008 3.37% 10.14% 0.66% 23.05 0.32 7704.21 0.06% 4805.62 37.80% 0.2241 23104.41 Modiin

2008 3.59% 1.23% 0.13% 29.86 0.28 6999.50 0.23% 9856.76 74.30% 0.2941 17710.30

Maale-Adummim 2008 3.36% 2.78% 0.23% 27.71 0.26 5552.77 0.19% 6398.11 59.40% 0.2623 18134.97 Ma’alot Tarshiha 2008 3.13% 9.39% 0.51% 25.94 0.30 5882.31 0.08% 5169.07 45.70% 0.2417 19837.36 Nahariya

2008 3.61% 8.01% 0.76% 27.31 0.36 5422.02 0.09% 6357.79 54.00% 0.2948 17830.30

Ness-Ziona

2008 2.98% 3.44% 0.56% 28.02 0.33 7315.87 0.25% 8289.72 55.80% 0.3527 24775.00

Nazareth

2008 1.96% 12.21% 0.37% 29.79 0.28 4128.86 0.04% 4355.33 42.90% 0.2844 13355.96

Nazareth-Illit

2008 3.45% 10.89% 0.98% 24.88 0.39 5265.44 0.07% 4782.66 50.00% 0.2413 18210.00

Nesher

2008 5.42% 6.20% 0.65% 27.01 0.42 7332.59 0.08% 6431.81 62.90% 0.3021 24611.84

Netivot

2008 4.30% 11.45% 0.34% 22.59 0.25 5861.29 0.09% 4054.92 33.00% 0.1681 18952.17

Netanya

2008 2.51% 7.29% 0.80% 26.80 0.35 5559.58 0.11% 5564.58 45.20% 0.2623 18538.35

Skhnen

2008 0.56% 18.27% 0.24% 31.15 0.24 5999.12 0.10% 3836.95 37.10% 0.2295 15653.16

Akko

2008 3.00% 17.49% 0.72% 25.99 0.33 6689.17 0.07% 4503.33 35.10% 0.2142 21268.37

Afula

2008 3.08% 8.84% 0.60% 24.36 0.36 7129.49 0.09% 4758.94 45.00% 0.2606 22146.03

Arad

2008 4.95% 9.87% 0.83% 23.61 0.37 5793.13 0.08% 5686.36 48.10% 0.2074 19617.81

Petah-Tikva

2008 2.98% 3.36% 0.68% 26.32 0.35 6035.23 0.15% 6473.14 52.80% 0.6057 20679.46

Zfat

2008 8.03% 13.13% 0.65% 23.04 0.34 6214.73 0.04% 4377.43 30.60% 0.1903 19933.67

Qalansuwa

2008 0.53% 12.99% 0.26% 32.89 0.18 3428.85 0.11% 3866.99 27.90% 0.1958 9909.31

Kiryat- Ono

2008 4.48% 1.78% 0.59% 29.81 0.38 6755.53 0.14% 9339.45 61.30% 0.3952 21758.02

kiryat-ata

2008 3.15% 8.42% 0.77% 26.02 0.36 6070.42 0.10% 5749.87 45.90% 0.2808 20550.04

Qiryat-Bialik

2008 5.06% 6.71% 0.98% 28.92 0.40 5310.60 0.09% 6339.89 49.10% 0.3205 18057.01

Qiryat-Gat

2008 3.27% 12.51% 0.70% 25.30 0.31 6117.45 0.07% 4283.38 46.00% 0.1921 21587.22

Qiryat-Yam

2008 4.99% 11.57% 1.09% 26.24 0.39 5526.85 0.06% 5020.33 38.00% 0.2246 18136.94

Kiriat-Motzkin

2008 4.88% 6.53% 0.83% 30.82 0.37 4963.27 0.09% 6567.83 53.80% 0.2832 17301.74

kiryat-malchy

2008 4.02% 16.59% 0.40% 23.68 0.28 9024.10 0.07% 4001.12 29.10% 0.2242 26195.74

kiryat-shmona

2008 3.79% 7.56% 0.56% 23.22 0.35 8378.68 0.07% 4843.79 43.40% 0.2830 24846.45

Rosh-Haayin

2008 3.25% 3.14% 0.35% 27.73 0.27 6932.40 0.11% 7142.81 50.70% 0.3206 22670.03

Rishon Lezion

2008 3.30% 3.95% 0.55% 28.48 0.31 4757.82 0.10% 7072.96 54.60% 0.3509 17637.87

Rahat

2008 0.49% 28.86% 0.27% 30.92 0.08 4028.05 0.17% 3584.18 24.70% 0.1333 12866.80

Rehovot

2008 3.90% 5.64% 0.63% 27.88 0.35 5655.50 0.10% 6996.33 50.20% 0.3036 19575.62

Ramla

2008 3.54% 7.09% 0.63% 25.46 0.27 5155.45 0.06% 4692.08 36.10% 0.2588 17390.87

Ramat-Gan

2008 5.47% 2.31% 0.89% 27.10 0.43 6174.25 0.10% 7621.22 65.60% 0.3820 22463.48

Ramat-Hasharon 2008 4.37% 1.20% 0.54% 27.56 0.36 9373.42 0.11% 10676.27 69.20% 0.4843 31185.27 Raanana

2008 4.59% 1.23% 0.45% 27.94 0.29 7383.13 0.08% 10102.80 70.00% 0.3767 27198.43

Sderot

2008 5.28% 10.38% 0.68% 21.52 0.32 7895.45 0.06% 4417.50 40.90% 0.2264 25164.65

Shefaram

2008 0.62% 17.28% 0.35% 31.09 0.24 4319.61 0.15% 4272.76 42.20% 0.2464 14148.12

Tel-Aviv

2008 5.45% 4.20% 0.93% 24.14 0.47 10503.32 0.10% 7780.98 58.40% 0.5925 35566.68


2007 3.84% 14.81% 0.68% 21.18 0.25 5765.02 0.08% 4226.35 31.00% 0.1550 11569.14

Or Yehuda

2007 3.38% 6.33% 0.61% 25.14 0.31 6571.42 0.12% 5478.12 37.20% 0.3148 13865.64

Or Akiva

2007 3.81% 11.68% 0.64% 22.02 0.30 6749.95 0.08% 4194.08 41.80% 0.2368 13992.22

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International Symposium on Stochastic Models in Reliability Engineering, Life Sciences and Operations Management (SMRLO'10) City

Year

X1

X2

X3

X4

X5

X6

Y1

Y2

Y3

Y4

Y5

Eilat

2007 10.49% 5.45% 0.38% 25.74 0.34 9775.43 0.11% 5150.50 49.30% 0.2864 22091.07

Ariel

2007 4.10% 3.66% 0.43% 26.77 0.27 6054.18 0.09% 5243.58 42.60% 0.2378 14106.72

Ashdod

2007 2.36% 9.72% 0.59% 26.48 0.29 4758.08 0.11% 5091.81 47.60% 0.1932 12479.80

Ashkelon

2007 2.55% 13.87% 0.74% 28.88 0.31 4781.68 0.10% 4780.43 46.80% 0.2312 11688.01

BakaJat

2007 0.55% 8.54% 0.35% 31.34 0.24 4643.00 0.13% 4365.51 41.50% 0.2409 8989.90

Beer-Sheva

2007 3.20% 12.08% 0.69% 26.41 0.37 5514.61 0.06% 5620.23 43.10% 0.2243 12955.26

Beit-Shean

2007 2.91% 10.29% 0.49% 21.24 0.28 9637.81 0.09% 4624.84 35.10% 0.2393 15766.02

Beit-Shemesh

2007 3.09% 4.96% 0.25% 24.27 0.23 4466.11 0.16% 4912.60 32.50% 0.1267 9050.65

Beitar-Illit

2007 2.50% 4.42% 0.08% 22.39 0.18 4823.16 0.20% 3197.23 32.50% 0.0533 6332.90

Bney-Brak

2007 3.74% 4.24% 0.48% 25.66 0.26 5173.50 0.08% 4514.19 32.50% 0.4731 11729.91

Bat-Yam

2007 4.59% 6.08% 1.04% 26.40 0.37 4958.59 0.08% 4586.62 43.60% 0.2466 11771.83

Givatayim

2007 6.10% 1.96% 1.05% 30.92 0.45 5998.44 0.12% 8259.25 66.60% 0.4071 13700.92

Dimona

2007 3.62% 17.95% 0.69% 24.59 0.33 5903.85 0.06% 5677.53 34.10% 0.1725 12518.99


2007 4.43% 1.99% 0.64% 27.40 0.39 7836.23 0.08% 8076.68 65.00% 0.5061 18810.79

Hadera

2007 3.08% 7.98% 0.69% 26.08 0.34 5741.28 0.09% 5301.80 45.60% 0.2895 13346.27

Holon

2007 3.67% 3.78% 0.75% 27.83 0.36 5003.69 0.09% 5678.08 48.80% 0.3517 12403.61

Haifa

2007 3.21% 7.98% 0.98% 25.75 0.42 7618.54 0.07% 6938.97 58.90% 0.3502 17267.25

Tiberias

2007 3.94% 12.62% 0.56% 24.46 0.35 6387.78 0.06% 4438.59 36.70% 0.2402 14632.41

Taibe

2007 0.40% 13.75% 0.34% 31.72 0.20 5383.81 0.12% 3938.88 32.50% 0.2290 4700.83

Tierra

2007 0.35% 4.15% 0.37% 28.66 0.25 4194.86 0.10% 4181.62 36.90% 0.2668 8477.00

Tirat-Carmel

2007 2.91% 11.68% 0.73% 22.31 0.33 7304.29 0.08% 4710.22 46.40% 0.2462 18785.79

Tamra

2007 0.50% 23.63% 0.23% 29.03 0.22 4873.81 0.12% 3621.66 42.90% 0.2131 9692.01

Yavne

2007 3.48% 7.40% 0.42% 26.78 0.27 6023.27 0.07% 6491.69 52.70% 0.3390 15322.93

Yehud

2007 4.00% 2.38% 0.49% 29.09 0.32 5833.91 0.08% 7496.08 58.10% 0.3859 13361.17

Jerusalem

2007 2.25% 4.27% 0.46% 26.18 0.26 5272.54 0.06% 5575.72 31.50% 0.2034 11294.58

Kfar-Saba

2007 3.69% 2.20% 0.59% 28.36 0.31 5645.17 0.10% 7502.91 65.40% 0.4124 13044.66

Karmiel

2007 3.82% 7.98% 0.69% 27.07 0.34 4790.15 0.08% 5664.58 49.20% 0.2502 11648.05

Lod

2007 4.08% 9.85% 0.65% 25.56 0.30 5331.43 0.06% 4720.34 38.40% 0.4202 12376.37


2007 3.35% 1.31% 0.09% 29.45 0.29 4988.70 0.28% 9280.00 76.70% 0.2987 11201.16


2007 3.86% 8.47% 0.88% 26.69 0.36 5404.66 0.10% 6190.95 53.00% 0.2937 11349.63

Ness-Ziona

2007 2.75% 4.36% 0.49% 27.55 0.32 7491.69 0.24% 7556.07 55.00% 0.3565 16905.03

Nazareth

2007 2.17% 18.49% 0.37% 29.67 0.28 3942.81 0.05% 4383.34 42.00% 0.2739 8725.22

Nazareth-Illit

2007 3.51% 13.06% 0.91% 26.05 0.39 5431.68 0.07% 4917.52 47.00% 0.2362 11834.19

Nesher

2007 4.41% 6.77% 0.68% 27.19 0.41 6286.14 0.09% 6251.48 60.70% 0.2994 14693.95

Netivot

2007 4.33% 12.97% 0.43% 22.56 0.26 5736.80 0.09% 3983.00 33.20% 0.1611 11997.82

Netanya

2007 2.61% 8.30% 0.80% 27.19 0.35 4993.63 0.10% 5241.44 43.90% 0.2584 12054.83

Skhnen

2007 0.51% 19.13% 0.28% 31.51 0.21 5662.27 0.11% 3753.30 37.10% 0.2223 10697.09

Akko

2007 2.88% 18.51% 0.78% 25.73 0.33 5346.91 0.07% 4531.23 37.10% 0.2102 12467.09

Afula

2007 3.12% 9.88% 0.65% 25.08 0.36 6248.25 0.09% 5077.78 46.70% 0.2579 12842.25

Arad

2007 5.30% 13.51% 0.75% 23.64 0.37 5901.65 0.06% 5531.71 50.20% 0.2084 12458.49

Petah-Tikva

2007 3.01% 3.25% 0.67% 26.49 0.35 5800.08 0.12% 6219.70 53.30% 0.5726 13728.57

Zfat

2007 5.51% 12.53% 0.62% 23.50 0.34 6438.91 0.07% 4427.93 32.80% 0.1839 13103.47

Qalansuwa

2007 0.48% 13.77% 0.25% 32.78 0.18 3460.11 0.15% 4093.00 27.80% 0.1903 6705.55

Kiryat- Ono

2007 4.28% 1.99% 0.67% 29.35 0.38 6819.38 0.13% 8539.01 63.20% 0.3971 14937.99

416

International Symposium on Stochastic Models in Reliability Engineering, Life Sciences and Operations Management (SMRLO'10) City kiryat-ata

Year

X1

X2

X3

X4

X5

X6

Y1

Y2

Y3

Y4

Y5

2007 3.07% 9.24% 0.75% 26.65 0.36 5536.75 0.10% 5572.76 46.70% 0.2775 13507.75

Qiryat-Bialik

2007 4.86% 7.61% 0.85% 29.52 0.40 5137.21 0.09% 6257.44 46.90% 0.3180 11811.60

Qiryat-Gat

2007 3.67% 13.80% 0.66% 25.18 0.31 6192.98 0.05% 4189.56 43.20% 0.1897 14900.79

Qiryat-Yam

2007 4.83% 12.47% 1.12% 26.91 0.39 5721.28 0.07% 5010.57 35.20% 0.2218 12345.43

Kiriat-Motzkin

2007 4.63% 7.14% 0.87% 30.98 0.37 4721.07 0.11% 6451.54 49.80% 0.2815 11689.02

kiryat-malchy

2007 4.34% 17.79% 0.61% 23.76 0.29 7686.50 0.07% 3920.29 29.90% 0.2186 15440.64

kiryat-shmona

2007 3.69% 8.20% 0.58% 24.08 0.35 7867.33 0.07% 4830.48 51.20% 0.2725 15627.54

Rosh-Haayin

2007 3.32% 3.45% 0.28% 27.07 0.27 6189.53 0.10% 6907.95 53.70% 0.3202 14317.89

Rishon Lezion

2007 3.23% 4.24% 0.55% 28.20 0.31 4800.22 0.10% 6620.68 55.60% 0.3494 12667.93

Rahat

2007 0.66% 29.91% 0.30% 30.84 0.08 3721.42 0.07% 3596.92 26.40% 0.1303 8398.82

Rehovot

2007 3.77% 6.61% 0.65% 27.94 0.35 6453.53 0.10% 6751.53 54.40% 0.3044 13353.42

Ramla

2007 3.78% 8.19% 0.67% 25.72 0.27 8669.89 0.06% 4459.08 33.50% 0.2541 14344.04

Ramat-Gan

2007 5.38% 2.62% 0.92% 26.75 0.44 6128.87 0.10% 7211.83 64.90% 0.3841 15008.28


2007 4.08% 1.42% 0.42% 27.92 0.30 7856.34 0.10% 9419.10 68.20% 0.3788 17121.83

Sderot

2007 4.59% 13.26% 0.64% 21.38 0.32 9007.15 0.08% 4264.63 36.60% 0.2197 19469.61

Shefaram

2007 0.74% 18.79% 0.34% 30.80 0.24 4376.51 0.15% 4372.88 36.70% 0.2429 9638.01

Tel-Aviv

2007 4.95% 4.66% 0.99% 24.25 0.47 9952.09 0.12% 7275.70 56.10% 0.5826 24263.23


2006 3.97% 15.43% 0.55% 21.93 0.25 6140.57 0.09% 4021.56 25.30% 0.1502 5746.55

Or Yehuda

2006 3.91% 6.78% 0.62% 24.89 0.31 5717.50 0.12% 5557.37 37.20% 0.3075 5401.72

Or Akiva

2006 3.92% 13.33% 0.58% 22.99 0.30 7337.37 0.09% 4124.33 35.60% 0.2324 6592.19

Eilat

2006 11.45% 5.42% 0.32% 25.13 0.35 8831.58 0.10% 5170.14 46.80% 0.2827 9009.97

Ariel

2006 5.31% 4.08% 0.46% 27.02 0.27 5536.68 0.07% 5306.77 42.40% 0.2352 5278.97

Ashdod

2006 2.35% 10.73% 0.59% 26.41 0.29 4720.83 0.13% 5168.95 44.90% 0.1903 4535.28

Ashkelon

2006 3.10% 15.67% 0.71% 29.05 0.32 4345.39 0.09% 4645.88 48.10% 0.2276 4373.55

BakaJat

2006 0.71% 9.53% 0.26% 31.44 0.23 4919.84 0.11% 3900.28 36.50% 0.2287 4234.01

Beer-Sheva

2006 3.55% 15.19% 0.71% 25.73 0.37 5368.67 0.07% 5467.78 41.30% 0.2214 5229.46

Beit-Shean

2006 3.70% 11.19% 0.42% 21.38 0.28 7908.85 0.04% 4329.42 35.00% 0.2359 6270.90

Beit-Shemesh

2006 3.62% 5.43% 0.27% 24.48 0.24 4493.94 0.20% 5016.11 34.90% 0.1304 4245.61

Beitar-Illit

2006 3.37% 4.68% 0.09% 22.34 0.19 4761.60 0.17% 3256.01 4.50% 0.0544 4532.36

Bney-Brak

2006 4.41% 4.50% 0.48% 25.01 0.26 5198.57 0.08% 4552.57 7.80% 0.4267 4694.89

Bat-Yam

2006 5.68% 7.05% 0.96% 26.12 0.37 4571.60 0.07% 4638.47 43.20% 0.2424 4596.63

Givatayim

2006 7.01% 2.23% 1.01% 29.67 0.46 5702.59 0.11% 8269.47 67.00% 0.4086 5315.72

Dimona

2006 3.84% 20.47% 0.77% 24.83 0.33 5711.13 0.05% 5330.98 37.70% 0.1653 5294.57


2006 4.86% 2.19% 0.65% 27.51 0.39 7273.56 0.08% 7997.90 65.00% 0.4821 7535.40

Hadera

2006 3.53% 9.50% 0.75% 26.36 0.34 5375.72 0.09% 5162.32 40.90% 0.2830 5235.46

Holon

2006 4.38% 4.39% 0.72% 27.70 0.35 4967.89 0.08% 5718.21 47.50% 0.3571 5035.63

Haifa

2006 3.48% 8.53% 0.95% 25.96 0.41 7408.64 0.08% 6643.68 57.40% 0.3455 7508.53

Tiberias

2006 4.84% 13.74% 0.58% 23.28 0.35 7001.30 0.05% 4309.33 30.30% 0.2371 6715.83

Taibe

2006 0.64% 13.49% 0.26% 31.39 0.19 2906.52 0.08% 3550.05 28.10% 0.2192 2801.85

Tierra

2006 0.56% 4.50% 0.32% 28.10 0.25 4657.80 0.15% 3845.52 37.80% 0.2471 3653.06

Tirat-Carmel

2006 3.22% 12.39% 0.78% 23.18 0.33 6998.89 0.08% 4541.03 38.50% 0.2440 6937.71

Tamra

2006 0.53% 24.50% 0.36% 28.55 0.22 4644.45 0.10% 3427.45 38.70% 0.2023 4291.62

Yavne

2006 4.47% 8.01% 0.43% 27.68 0.27 6024.00 0.07% 6442.54 50.40% 0.3338 6110.68

Yehud

2006 4.69% 2.71% 0.56% 28.72 0.32 5899.54 0.09% 7613.75 57.50% 0.3860 5259.71

Jerusalem

2006 2.56% 4.49% 0.45% 25.86 0.26 4424.60 0.06% 5669.84 31.70% 0.2023 4321.84

417

International Symposium on Stochastic Models in Reliability Engineering, Life Sciences and Operations Management (SMRLO'10) City Kfar-Saba

Year

X1

X2

X3

X4

X5

X6

Y1

Y2

Y3

Y4

Y5

2006 3.94% 2.41% 0.60% 28.72 0.31 5668.50 0.10% 7544.79 65.30% 0.4167 6345.94

Karmiel

2006 3.54% 8.72% 0.66% 27.13 0.33 5069.12 0.11% 5434.60 48.30% 0.2459 5260.46

Lod

2006 5.09% 10.83% 0.61% 25.16 0.30 5035.33 0.06% 4800.29 34.70% 0.4074 4427.78


2006 4.03% 1.33% 0.14% 30.21 0.30 5082.54 0.24% 9652.30 72.90% 0.3005 5016.07


2006 3.89% 9.04% 0.80% 27.70 0.36 5400.13 0.12% 6111.42 50.10% 0.2873 5429.66

Ness-Ziona

2006 3.35% 4.78% 0.50% 26.91 0.34 7458.10 0.21% 7484.89 55.20% 0.3497 7623.72

Nazareth

2006 1.78% 20.65% 0.34% 29.27 0.28 4140.83 0.07% 4198.90 40.00% 0.2626 3436.44

Nazareth-Illit

2006 3.73% 14.34% 0.93% 27.36 0.38 7506.09 0.08% 4621.52 51.00% 0.2303 7612.51

Nesher

2006 5.53% 7.30% 0.61% 26.68 0.41 6298.01 0.09% 6044.25 51.80% 0.2998 6909.04

Netivot

2006 4.21% 13.40% 0.40% 22.28 0.26 5400.69 0.11% 3759.65 26.30% 0.1582 5582.78

Netanya

2006 3.00% 9.15% 0.76% 27.18 0.35 4885.10 0.11% 5210.34 45.90% 0.2517 4812.54

Skhnen

2006 0.68% 19.65% 0.25% 31.02 0.21 4255.24 0.10% 3434.83 24.50% 0.2104 4294.47

Akko

2006 3.60% 19.09% 0.82% 25.02 0.32 5880.38 0.07% 4435.51 32.90% 0.2079 5215.99

Afula

2006 3.56% 11.49% 0.66% 24.96 0.36 5958.57 0.08% 4820.73 42.20% 0.2518 5931.07

Arad

2006 6.76% 22.37% 0.66% 23.24 0.36 5529.28 0.04% 5358.44 47.70% 0.2042 4854.75

Petah-Tikva

2006 3.41% 3.36% 0.71% 26.37 0.35 6125.10 0.11% 6206.13 53.00% 0.5408 5911.18

Zfat

2006 7.29% 13.38% 0.64% 23.32 0.35 6705.75 0.06% 4238.11 30.70% 0.1866 6778.28

Qalansuwa

2006 0.68% 13.76% 0.24% 31.90 0.19 3627.31 0.12% 3832.13 30.70% 0.1783 3448.67

Kiryat- Ono

2006 5.21% 2.21% 0.57% 29.28 0.38 6409.95 0.12% 8345.80 60.90% 0.3969 5982.21

kiryat-ata

2006 3.76% 9.79% 0.76% 26.21 0.36 5897.98 0.09% 5307.11 42.50% 0.2722 5691.01

Qiryat-Bialik

2006 5.60% 8.12% 0.87% 29.56 0.39 4860.59 0.08% 5926.38 50.10% 0.3141 4743.52

Qiryat-Gat

2006 4.04% 14.72% 0.66% 25.29 0.30 6221.10 0.05% 4254.37 43.30% 0.1839 5850.21

Qiryat-Yam

2006 5.40% 12.99% 1.04% 26.55 0.38 5169.58 0.07% 4782.72 40.60% 0.2194 4797.98

Kiriat-Motzkin

2006 5.47% 7.73% 0.87% 29.45 0.37 4507.54 0.08% 6109.22 50.50% 0.2846 4224.28

kiryat-malchy

2006 4.71% 18.84% 0.52% 23.61 0.29 7513.38 0.08% 3937.17 28.50% 0.2119 6970.30

kiryat-shmona

2006 4.25% 8.91% 0.52% 23.37 0.34 7824.78 0.08% 4613.46 42.30% 0.2677 7282.38

Rosh-Haayin

2006 3.95% 3.57% 0.34% 27.45 0.28 6158.39 0.09% 7009.25 48.10% 0.3143 6258.82

Rishon Lezion

2006 3.81% 4.70% 0.52% 28.34 0.31 4941.75 0.11% 6790.28 54.80% 0.3456 5211.72

Rahat

2006 0.78% 32.02% 0.35% 30.36 0.08 3369.27 0.09% 3621.49 16.30% 0.1230 3593.39

Rehovot

2006 3.96% 7.57% 0.73% 28.40 0.35 5818.41 0.12% 6736.51 52.30% 0.2984 5713.27

Ramla

2006 3.96% 9.31% 0.60% 26.60 0.27 5506.30 0.08% 4533.86 31.00% 0.2481 5131.61

Ramat-Gan

2006 6.22% 3.01% 0.87% 26.89 0.44 5935.48 0.10% 7191.15 63.20% 0.3875 5987.96


2006 4.72% 1.56% 0.47% 27.82 0.30 6437.40 0.09% 9269.74 68.40% 0.3848 6786.28

Sderot

2006 4.13% 15.51% 0.64% 21.61 0.32 7718.35 0.09% 4135.18 30.30% 0.2074 7083.78

Shefaram

2006 0.97% 19.29% 0.33% 30.99 0.24 5364.56 0.13% 4233.62 40.60% 0.2368 5057.73

Tel-Aviv

2006 5.52% 5.24% 0.97% 24.20 0.48 9785.80 0.12% 7208.46 55.70% 0.5957 9799.20

Table 2. Score and Malmquist productivity change index Cross Efficiency

Malmquist productivity

City

Umm elFaheim OFAKIM

2008

2007

2006

Mean

Rank

20062007

20072008

Mean

0.7547

0.7442

0.7667

0.755

54

0.777

0.561

0.660

0.7228

0.7201

0.7491

0.731

63

0.723

0.570

0.642

418

International Symposium on Stochastic Models in Reliability Engineering, Life Sciences and Operations Management (SMRLO'10) Cross Efficiency


City 2008

2007

2006

Mean

Rank

20062007

20072008

Mean

Or Yehuda

0.8159

0.7957

0.7897

0.800

31

0.738

0.615

0.674

Or Akiva

0.7936

0.7644

0.7603

0.773

47

0.742

0.587

0.660

Eilat

0.7003

0.8116

0.793

0.768

49

0.631

0.546

0.587

Ariel

0.7957

0.8402

0.7509

0.796

35

0.724

0.528

0.618

Ashdod

0.8472

0.9064

0.7849

0.846

17

0.852

0.534

0.675

Ashkelon

0.8466

0.8264

0.7591

0.811

27

0.803

0.584

0.685

BakaJat

0.8778

0.7549

0.7564

0.796

33

0.406

0.644

0.511

Beer-Sheva

0.7977

0.8083

0.7616

0.789

39

0.752

0.548

0.642

Beit-Shean

0.6782

0.6852

0.717

0.693

68

0.696

0.504

0.592

Beit-Shemesh

0.8029

0.7389

0.7532

0.765

50

0.781

0.710

0.745

Beitar-Illit

0.6603

0.542

0.7139

0.639

69

1.018

0.669

0.826

Bney-Brak

0.8154

0.8219

0.7441

0.794

36

0.824

0.668

0.742

Bat-Yam

0.769

0.7696

0.7162

0.752

55

0.794

0.580

0.679

Givatayim

0.8018

0.811

0.7614

0.791

37

0.921

0.681

0.792

Dimona

0.781

0.7421

0.7246

0.749

56

0.701

0.572

0.633

Hod-Hasharon

0.9233

0.8963

0.8867

0.902

8

0.849

0.644

0.740

Herzliya

0.8883

0.9334

0.913

0.912

5

0.833

0.615

0.716

Hadera

0.8083

0.8322

0.7795

0.807

29

0.775

0.555

0.656

Holon

0.8495

0.8551

0.8034

0.836

20

0.833

0.611

0.713

Haifa

0.8436

0.8637

0.8707

0.859

16

0.828

0.613

0.712

Tiberias

0.6754

0.7921

0.7588

0.742

60

0.785

0.515

0.636

Taibe

0.7184

0.4331

0.7628

0.638

70

0.552

0.844

0.682

Tierra

0.8151

0.7819

0.73

0.776

45

0.944

0.608

0.758

Tirat-Carmel

0.8799

0.9465

0.8279

0.885

11

0.781

0.475

0.609

Tamra

0.782

0.7622

0.7889

0.778

44

0.869

0.573

0.705

Yavne

0.915

0.9477

0.8557

0.906

6

0.784

0.592

0.681

Yehud

0.7135

0.8669

0.792

0.791

38

0.847

0.642

0.738

Jerusalem

0.7832

0.7935

0.7899

0.789

40

0.779

0.606

0.687

Kfar-Saba

0.8421

0.893

0.9577

0.898

10

0.914

0.679

0.788

Karmiel

0.8669

0.8245

0.8146

0.835

21

0.802

0.581

0.682

Lod MigdalHaemeq

0.8172

0.811

0.7231

0.784

41

0.778

0.629

0.699

0.7331

0.8169

0.7389

0.763

52

0.792

0.526

0.646

0.7887

0.9351

0.9014

0.875

13

1.063

0.556

0.769

0.8798

0.851

0.9015

0.877

12

0.815

0.667

0.737

0.823

0.8187

0.8017

0.814

25

0.755

0.598

0.672

Modiin MaaleAdummim Ma’alot Tarshiha Nahariya

0.829

0.7635

0.8065

0.800

32

0.815

0.653

0.730

Ness-Ziona

0.9108

0.9168

0.9268

0.918

3

0.843

0.603

0.713

Nazareth

0.7881

0.7453

0.6936

0.742

59

0.852

0.650

0.744 0.692

Nazareth-Illit

0.829

0.7452

0.8145

0.796

34

0.739

0.647

Nesher

0.8327

0.8329

0.8452

0.837

19

0.832

0.616

0.716

Netivot

0.7583

0.734

0.7855

0.759

53

0.668

0.570

0.617

Netanya

0.8271

0.833

0.7818

0.814

26

0.787

0.554

0.661

Skhnen

0.686

0.7354

0.808

0.743

58

0.794

0.573

0.675

Akko

0.7486

0.7878

0.7028

0.746

57

0.750

0.487

0.604

419



City 2008

2007

2006

Mean

Rank

20062007

20072008

Mean

Afula

0.7735

0.7568

0.7951

0.775

46

0.770

0.622

0.692

Arad

0.8106

0.7346

0.6671

0.737

62

0.783

0.624

0.699

Petah-Tikva

0.9157

0.9086

0.8788

0.901

9

0.846

0.653

0.743 0.613

Zfat

0.7006

0.6958

0.7388

0.712

66

0.659

0.571

Qalansuwa

0.7304

0.7151

0.7688

0.738

61

0.949

0.667

0.796

Kiryat- Ono

0.8552

0.8515

0.8136

0.840

18

0.823

0.645

0.728

kiryat-ata

0.8318

0.8541

0.7754

0.820

23

0.785

0.528

0.644

Qiryat-Bialik

0.8093

0.769

0.7334

0.771

48

0.786

0.637

0.707

Qiryat-Gat

0.834

0.828

0.7431

0.802

30

0.707

0.527

0.610

Qiryat-Yam

0.7454

0.7074

0.6776

0.710

67

0.672

0.565

0.616

Kiriat-Motzkin

0.8299

0.8101

0.7097

0.783

42

0.848

0.608

0.718

kiryat-malchy

0.6894

0.7275

0.7591

0.725

65

0.630

0.533

0.580

kiryat-Shmona

0.7394

0.7617

0.7934

0.765

51

0.809

0.630

0.714

Rosh-Haayin

0.8454

0.9006

0.8781

0.875

14

0.792

0.601

0.690

Rishon Lezion

0.9341

0.9419

0.8739

0.917

4

0.847

0.611

0.720

Rahat

0.7923

0.8102

0.8267

0.810

28

0.674

0.662

0.668

Rehovot

0.8574

0.7841

0.812

0.818

24

0.741

0.652

0.695

Ramla

0.7926

0.6538

0.7399

0.729

64

0.672

0.546

0.606

Ramat-Gan RamatHasharon

0.9114

0.8701

0.8126

0.865

15

0.822

0.649

0.730

0.9001

0.9564

0.9233

0.927

2

0.779

0.601

0.684

0.9631

0.9093

0.9432

0.939

1

0.791

0.612

0.695

Raanana Sderot

0.7598

0.8104

0.7684

0.780

43

0.786

0.469

0.607

Shefaram

0.8488

0.8041

0.8143

0.822

22

0.793

0.639

0.712

Tel-Aviv

0.8686

0.9401

0.9029

0.904

7

0.820

0.616

0.711

Mean

0.808

0.805

0.793

0.802

0.778

0.598

0.682

• Note that all Malmquist index averages are geometric means. • The results of Malmquist index from DEAP version 2.1 Table 3. 10 top ranked Israeli cities Malmquist productivity

Cross Efficiency

City 2008

2007

2006

Mean

Rank

20062007

20072008

Mean*

Raanana

0.9631

0.9093

0.9432

0.939

1

0.791

0.612

0.695

Ramat-Hasharon

0.9001

0.9564

0.9233

0.927

2

0.779

0.601

0.684

Ness-Ziona Rishon Lezion

0.9108 0.9341

0.9168 0.9419

0.9268 0.8739

0.918 0.917

3 4

0.843 0.847

0.603 0.611

0.713 0.720

Herzliya

0.8883

0.9334

0.913

0.912

5

0.833

0.615

0.716

Yavne

0.915

0.9477

0.8557

0.906

6

0.784

0.592

0.681

Tel-Aviv Hod-Hasharon

0.8686 0.9233

0.9401 0.8963

0.9029 0.8867

0.904 0.902

7 8

0.82 0.849

0.616 0.644

0.711 0.740

Petah-Tikva

0.9157

0.9086

0.8788

0.901

9

0.846

0.653

0.743

420


City

Kfar-Saba


2008

2007

2006

Mean

Rank

20062007

20072008

Mean*

0.8421

0.893

0.9577

0.898

10

0.914

0.679

0.788

• Note that according to the Cross Efficiency method results Raanana, Ramat-Hasharon and Ness-Ziona turned out to be ranked first. The common feature of these cities is their geographical position in the centre of the country and along the sea coast line.

Table 4. 10 bottom ranked Israeli cities

Qalansuwa


Cross Efficiency

City 2008

2007

2006

Mean

Rank

20062007

20072008

Mean*

0.7304

0.7151

0.7688

0.738

61

0.949

0.667

0.796

Arad

0.8106

0.7346

0.6671

0.737

62

0.783

0.624

0.699

Ofakim

0.7228

0.7201

0.7491

0.731

63

0.723

0.57

0.642

Ramla

0.7926

0.6538

0.7399

0.729

64

0.672

0.546

0.606

Kiryat-Mal'achy

0.6894

0.7275

0.7591

0.725

65

0.63

0.533

0.580

Zfat

0.7006

0.6958

0.7388

0.712

66

0.659

0.571

0.613

Qiryat-Yam

0.7454

0.7074

0.6776

0.71

67

0.672

0.565

0.616

Beit-Shean

0.6782

0.6852

0.717

0.693

68

0.696

0.504

0.592

Beitar-Illit

0.6603

0.542

0.7139

0.639

69

1.018

0.669

0.826

Taibe

0.7184

0.4331

0.7628

0.638

70

0.552

0.844

0.682

• Note that bottom ranked cities listed in Table 4 belong generally to the northern and southern outskirts of the country.

5. Conclusions and Future Research In this paper we intended to demonstrate an important application area of the DEA methodology enabling relative effectively assessment of DMUs in conjunction with the CE method to carry out fully ranking for the same, all this compared with the Malmquist productivity index capable of evaluating relative improvement of each DMU per every pair of consecutive time periods. These methods have been applied to evaluating 70 Israeli cities within years 2006, 2007 and 2008. The results obtained which have been reported in the present study may lead to the following conclusions: • No correlation whatsoever has been identified between the ranking position of the city and its relative improvement through years. As a matter of fact, the majority of cities investigated in our research show actually worsening rather than improvement, no matter whether being ranked at the top of the list or close to the bottom. • Ranking positions obtained as well as improvement rates refer of cause to the set of input / output criteria chosen for the research. A different choice of input / output criteria might cause other results, accordingly.

421

International Symposium on Stochastic Models in Reliability Engineering, Life Sciences and Operations Management (SMRLO'10) • There is no consistency within the ranking obtained on the basis of existing ranking methods. The substance of the ranking method is important for obtaining specific ranking results whatsoever. • No correlation whatsoever has been identified between the size of the city (number of inhabitants) and its ranking / relative improvement through years. In other words, one cannot claim those features to be size dependent. Ranking and improvement as reflected in our research relate to a broad spectrum of instances such as: education, health care, the local authority's municipal spending, etc. We suggest further research to be undertaken to estimate ranking of cities according to each criterion separately, while calculating relative weights for every criterion chosen. Then, efficiency score and ranking position for every participating city might be re-calculated with reference to the established weights. In addition, further investigation has to be undertaken as to specific reasons for cities' productivity worsening as detected in the framework of the current research.

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